With the growth in human pressures on the marine environment and the increase in competition for space and resources there has been recognition by many governments of the need to use the marine environment sustainably and allow for its acceptable allocation for each sector. The aim of this thesis is to evaluate the use of Marxan and Marxan with Zones as practical tools to enable the production of marine plans that integrate environmental and socioeconomic data and to suggest best practice in the types of data used. In this thesis three key aspects of data type and integration were identified and evaluated. The resolution and complexity of data required to protected marine biodiversity was assessed. The effects of using different substrate data resolution on the selection of sites to protect a range of biotopes using Marxan are determined. The nature of the data used in marine planning has significant implications for the protection of marine biodiversity. Using less complex data, of any resolution, did not adequately protect marine biodiversity. There is a need to determine what is an acceptable allocation of marine resource to each sector. Two case study areas were used to determine how to integrate conservation and socioeconomic data and objectives in a marine plan. Objectives for all the sectors could not be met completely in a single marine plan and each sector had to compromise. This research highlighted the potential compromises required and indicates that if marine heritage and biodiversity are to be protected each sector will have to change the impact it has on the marine environment. Currently marine conservation assumes that all data on habitats and species presented for use in marine planning are equal, in accuracy, precision and value. This is not always the case, with data based on a wide range of sources including routine government monitoring, specific innovative research and stakeholder based data gathering. A case study area was used to evaluate the impacts of using confidence levels in habitat data on marine biodiversity. It was found that data outputs that best protected marine biodiversity used data over 20% and over 30% confidence. With the data currently available for the UK marine environment it is not possible to be confident that a representative MPA network can be created. Together these studies contribute key recommendations for best practice in marine planning and demonstrate that the use of spatial decision support tools (Marxan and Marxan with Zones) are essential for the integration of data in marine planning, to assess how using different types of data will impact marine planning and marine biodiversity protection and to explore implications of different management actions.